PROPOSING ALGORITHM TO IMPROVE STUDENT EVALUATION PROCESS

In this paper we propose an algorithm to improve the virtual learning assessment based on student tests history. By annotating each question in a quiz with elements which include the difficulty and domain of applicability and by logging student grade for each question, we get datasets that can be used to monitor student improvement over time and to check on their performance in each area or domain of expertise. The algorithm can be used to improve areas where students are less knowledgeable by providing quizzes which address these particular areas taking into account their previous results and, by integrating big data technologies and machine learning, we get new information insights. Applying this algorithm, the evaluation process will be improved because the quizzes are personalized for each student based on his experience and the continuous monitoring of student performance.